Initializing Adam's second-order moment estimate to a non-zero value, rather than the default zero, reduces early training instability and improves generalization across several deep learning tasks.
Neuralnetworksformachinelearning lecture 6a overview of mini-batch gradient descent.Cited on, 14(8):2, 2012
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Revisiting the Initial Steps in Adaptive Gradient Descent Optimization
Initializing Adam's second-order moment estimate to a non-zero value, rather than the default zero, reduces early training instability and improves generalization across several deep learning tasks.